scholarly journals Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases

2019 ◽  
Author(s):  
Scott C. Ritchie ◽  
Yingying Liu ◽  
Samuel A. Lambert ◽  
Shu Mei Teo ◽  
Petar Scepanovic ◽  
...  
Keyword(s):  
Dietary Intervention ◽  
Disease Risk ◽  
Therapeutic Potential ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Disease Biology ◽  
Genome Wide ◽  
Associated Proteins ◽  
Artery Disease

AbstractPolygenic risk scores (PRSs) capture the genetic architecture of common diseases by aggregating genome-wide genetic variation into a single score that reflects an individual’s disease risk. These present new opportunities to identify molecular pathways involved in disease pathogenesis. We performed association analysis between PRSs and 3,442 plasma proteins in 3,175 healthy individuals, identifying 48 proteins whose levels associated with PRSs for coronary artery disease, chronic kidney disease, or type 2 diabetes. Integrative analyses of human and mouse data to characterise these associations revealed a role for polygenic effects on several well-known causal disease proteins and identified promising novel targets for future follow-up. We found implicated PRS-associated genes were responsive to dietary intervention in mice and showed strong evidence of druggability in humans, consistent with PRS-associated proteins having therapeutic potential. Overall, our study provides a framework for polygenic association studies, demonstrating the power of PRSs to unravel novel disease biology.

scholarly journals Age-related late-onset disease heritability patterns and implications for genome-wide association studies

2018 ◽  
Author(s):  
Roman Teo Oliynyk
Keyword(s):  
Old Age ◽  
Cumulative Incidence ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cerebral Stroke ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

AbstractBackgroundGenome-wide association studies and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called “missing heritability” problem.MethodsComputer simulations of polygenic late-onset diseases in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes.ResultsThe incidence rate for late-onset diseases grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for genome-wide association studies overrepresent older individuals with lower polygenic risk scores, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and genome-wide association studies. It also explains the relatively constant-with-age heritability found for late-onset diseases of lower prevalence, exemplified by cancers.ConclusionsFor late-onset polygenic diseases showing high cumulative incidence together with high initial heritability, rather than using relatively old age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

scholarly journals CONVERGENT AGING LOCI: PATHWAYS THAT TRANSCEND INDIVIDUAL DISEASES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S221-S221
Author(s):  
Luke C Pilling ◽  
Luigi Ferrucci ◽  
David Melzer
Keyword(s):  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Telomere Shortening ◽  
Chronic Disease Risk ◽  
Trade Offs ◽  
Age Related ◽  
Genome Wide ◽  
Artery Disease

Abstract Thousands of loci across the genome have been identified for specific diseases in genome-wide association studies (GWAS), yet very few are associated with lifespan itself. We hypothesized that specific biological pathways transcend individual diseases and affect health and lifespan more broadly. Using the published results for the most recent GWAS for 10 key age-related diseases (including coronary artery disease, type-2 diabetes, and several cancers) we identified 22 loci with a strong genetic association with at least three of the diseases. These multi-trait aging loci include known genes affecting multiple diverse health end points, such as CDKN2A/B (9p21.3) and APOE. There are also novel multi-trait genes including SH2B3 and CASC8, likely involved in hallmark pathways of aging biology, including telomere shortening and inflammation. Several of these loci involve trade-offs between chronic disease risk and cancer.

scholarly journals Perspective: The Clinical Use of Polygenic Risk Scores: Race, Ethnicity, and Health Disparities

2019 ◽  
Vol 29 (3) ◽  
pp. 513-516 ◽  
Author(s):  
Megan C. Roberts ◽  
Muin J. Khoury ◽  
George A. Mensah
Keyword(s):  
Precision Medicine ◽  
Association Studies ◽  
Clinical Care ◽  
Genomic Research ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Adverse Health Outcomes ◽  
Genome Wide ◽  
Disease Risks

Polygenic risk scores (PRS) are an emerging precision medicine tool based on multiple gene variants that, taken alone, have weak associations with disease risks, but collec­tively may enhance disease predictive value in the population. However, the benefit of PRS may not be equal among non-European populations, as they are under-represented in genome-wide association studies (GWAS) that serve as the basis for PRS develop­ment. In this perspective, we discuss a path forward, which includes: 1) inclusion of underrepresented populations in PRS research; 2) global efforts to build capacity for genomic research; 3) equitable imple­mentation of these tools in clinical practice; and 4) traditional public health approaches to reduce risk of adverse health outcomes as an important component to precision health. As precision medicine is imple­mented in clinical care, researchers must ensure that advances from PRS research will benefit all.Ethn Dis.2019;29(3):513-516; doi:10.18865/ed.29.3.513.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

scholarly journals Polygenic risk scores for psychiatric, inflammatory, and cardio-metabolic traits and diseases highlight possible genetic overlaps with suicide attempt and treatment-emergent suicidal ideation

2021 ◽  
Author(s):  
Giuseppe Fanelli ◽  
Marcus Sokolowski ◽  
Danuta Wasserman ◽  
Siegfried Kasper ◽  
Joseph Zohar ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Suicide Attempt ◽  
Association Studies ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genetic Covariance ◽  
Polygenic Risk ◽  
Metabolic Traits ◽  
Gene Sets ◽  
Artery Disease

AbstractSuicide is the second leading cause of death among young people. Genetics may contribute to suicidal phenotypes and their co-occurrence in other psychiatric and medical conditions. Our study aimed to investigate the association of polygenic risk scores (PRSs) for 22 psychiatric, inflammatory, and cardio-metabolic traits and diseases with suicide attempt (SA) or treatment-worsening/emergent suicidal ideation (TWESI).PRSs were computed based on summary statistics of genome-wide association studies. Regression analyses were performed between PRSs and SA or TWESI in four clinical cohorts, including up to 3,834 individuals, and results were meta-analyzed across samples. Stratified genetic covariance analyses were performed to investigate the biology underlying cross-phenotype PRS associations. After Bonferroni correction, PRS for major depressive disorder (MDD) was positively associated with SA (p=1.7e-4). Nominal associations were shown between PRSs for coronary artery disease (CAD) (p=4.6e-3) or loneliness (p=0.009) and SA, PRSs for MDD or CAD and TWESI (p=0.033 and p=0.032, respectively). Genetic covariance between MDD and SA was shown in 35 gene sets related to drugs having anti-suicidal effects.A higher genetic liability for MDD may underlie a higher risk of SA. Further, but milder, possible modulatory factors are genetic risk for loneliness and CAD.

scholarly journals Validation of genome-wide polygenic risk scores for coronary artery disease in French Canadians

2019 ◽  
Author(s):  
Florian Wünnemann ◽  
Ken Sin Lo ◽  
Alexandra Langford-Avelar ◽  
David Busseuil ◽  
Marie-Pierre Dubé ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Scores ◽  
French Canadian ◽  
French Canadians ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Artery Disease ◽  
The Impact ◽  
Cad Risk

AbstractCoronary artery disease (CAD) represents one of the leading causes of morbidity and mortality worldwide. Given the healthcare risks and societal impacts associated with CAD, their clinical management would benefit from improved prevention and prediction tools. Polygenic risk scores (PRS) based on an individual’s genome sequence are emerging as potentially powerful biomarkers to predict the risk to develop CAD. Two recently derived genome-wide PRS have shown high specificity and sensitivity to identify CAD cases in European-ancestry participants from the UK Biobank. However, validation of the PRS predictive power and transferability in other populations is now required to support their clinical utility. We calculated both PRS (GPSCAD and metaGRSCAD) in French-Canadian individuals from three cohorts totaling 3639 prevalent CAD cases and 7382 controls, and tested their power to predict prevalent, incident and recurrent CAD. We also estimated the impact of the founder French-Canadian familial hypercholesterolemia deletion (LDLR delta > 15kb deletion) on CAD risk in one of these cohorts and used this estimate to calibrate the impact of the PRS. Our results confirm the ability of both PRS to predict prevalent CAD comparable to the original reports (area under the curve (AUC) = 0.72-0.84). Furthermore, the PRS identified about 6-7% of individuals at CAD risk similar to carriers of the LDLR delta > 15kb mutation, consistent with previous estimates. However, the PRS did not perform as well in predicting incident (AUC= 0.56 - 0.60) or recurrent (AUC= 0.56 - 0.60) CAD. This result suggests that additional work is warranted to better understand how ascertainment biases and study design impact PRS for CAD. Collectively, our results confirm that novel, genome-wide PRS are able to predict CAD in French-Canadians; with further improvements, this is likely to pave the way towards more targeted strategies to predict and prevent CAD-related adverse events.

scholarly journals Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestries

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Yanyu Liang ◽  
Milton Pividori ◽  
Ani Manichaikul ◽  
Abraham A. Palmer ◽  
Nancy J. Cox ◽  
...  
Keyword(s):  
Association Studies ◽  
Poor Performance ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Transcript Levels ◽  
Polygenic Risk ◽  
Genome Wide

Abstract Background Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry. Results We introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data. Conclusions We show that PTRS has a significantly higher portability (Wilcoxon p=0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.

scholarly journals Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-wide Association Studies of Late-onset Diseases

2019 ◽  
Author(s):  
Roman Teo Oliynyk
Keyword(s):  
Cumulative Incidence ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cerebral Stroke ◽  
Genome Wide Association Studies ◽  
Risk Alleles ◽  
Genome Wide ◽  
Artery Disease

AbstractFor more than a decade, genome-wide association studies have been making steady progress in discovering the causal gene variants that contribute to late-onset human diseases. Polygenic late-onset diseases in an aging population display the risk allele frequency decrease at older ages, caused by individuals with higher polygenic risk scores becoming ill proportionately earlier and bringing about a change in the distribution of risk alleles between new cases and the as-yet-unaffected population. This phenomenon is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes, while for late-onset diseases with relatively lower prevalence and heritability, exemplified by cancers, the effect is significantly lower. Computer simulations have determined that genome-wide association studies of the late-onset polygenic diseases showing high cumulative incidence together with high initial heritability will benefit from using the youngest possible age-matched cohorts. Moreover, rather than using age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

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